AIMC Topic: Reproducibility of Results

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EMG gesture signal analysis towards diagnosis of upper limb using dual-pathway convolutional neural network.

Mathematical biosciences and engineering : MBE
This research introduces a novel dual-pathway convolutional neural network (DP-CNN) architecture tailored for robust performance in Log-Mel spectrogram image analysis derived from raw multichannel electromyography signals. The primary objective is to...

Artificial Intelligence in Cataract Surgery: A Systematic Review.

Translational vision science & technology
PURPOSE: The purpose of this study was to assess the current use and reliability of artificial intelligence (AI)-based algorithms for analyzing cataract surgery videos.

Automatic pterygopalatine fossa segmentation and localisation based on DenseASPP.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: Allergic rhinitis constitutes a widespread health concern, with traditional treatments often proving to be painful and ineffective. Acupuncture targeting the pterygopalatine fossa proves effective but is complicated due to the intricate n...

Evaluating insomnia queries from an artificial intelligence chatbot for patient education.

Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine
STUDY OBJECTIVES: We evaluated the accuracy of ChatGPT in addressing insomnia-related queries for patient education and assessed ChatGPT's ability to provide varied responses based on differing prompting scenarios.

[Development and Application of Deep Learning-Based Model for Quality Control of Children Pelvic X-Ray Images].

Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation
OBJECTIVE: A deep learning-based method for evaluating the quality of pediatric pelvic X-ray images is proposed to construct a diagnostic model and verify its clinical feasibility.

HyGAnno: hybrid graph neural network-based cell type annotation for single-cell ATAC sequencing data.

Briefings in bioinformatics
Reliable cell type annotations are crucial for investigating cellular heterogeneity in single-cell omics data. Although various computational approaches have been proposed for single-cell RNA sequencing (scRNA-seq) annotation, high-quality cell label...

Arrhythmia classification based on multi-feature multi-path parallel deep convolutional neural networks and improved focal loss.

Mathematical biosciences and engineering : MBE
Early diagnosis of abnormal electrocardiogram (ECG) signals can provide useful information for the prevention and detection of arrhythmia diseases. Due to the similarities in Normal beat (N) and Supraventricular Premature Beat (S) categories and imba...

Deep CNNs for glioma grading on conventional MRIs: Performance analysis, challenges, and future directions.

Mathematical biosciences and engineering : MBE
The increasing global incidence of glioma tumors has raised significant healthcare concerns due to their high mortality rates. Traditionally, tumor diagnosis relies on visual analysis of medical imaging and invasive biopsies for precise grading. As a...

A novel lightweight deep learning approach for simultaneous optic cup and optic disc segmentation in glaucoma detection.

Mathematical biosciences and engineering : MBE
Glaucoma is a chronic neurodegenerative disease that can result in irreversible vision loss if not treated in its early stages. The cup-to-disc ratio is a key criterion for glaucoma screening and diagnosis, and it is determined by dividing the area o...

Deep Learning to Differentiate Benign and Malignant Vertebral Fractures at Multidetector CT.

Radiology
Background Differentiating between benign and malignant vertebral fractures poses diagnostic challenges. Purpose To investigate the reliability of CT-based deep learning models to differentiate between benign and malignant vertebral fractures. Materi...